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Search results for pytorch anomaly detection
anomaly-detection
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pytorch
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93 search results found
Flow Forecast
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1,759
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
Ailia Models
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1,708
The collection of pre-trained, state-of-the-art AI models for ailia SDK
Pygod
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1,138
A Python Library for Graph Outlier Detection (Anomaly Detection)
Training_extensions
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1,119
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Getting Things Done With Pytorch
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873
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
Ganomaly
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767
GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training
Deep Svdd Pytorch
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538
A PyTorch implementation of the Deep SVDD anomaly detection method
Outlier Exposure
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378
Deep Anomaly Detection with Outlier Exposure (ICLR 2019)
Deeplog
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320
Pytorch Implementation of DeepLog.
Deepadots
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270
Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
Deep Sad Pytorch
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268
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Mtad Gat Pytorch
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265
PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).
Rtfm
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233
Official code for 'Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning' [ICCV 2021]
Pytorch_cpp
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215
Deep Learning sample programs using PyTorch in C++
Fcdd
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204
Repository for the Explainable Deep One-Class Classification paper
Pytorch Ood
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166
👽 Out-of-Distribution Detection with PyTorch
Skip Ganomaly
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144
Source code for Skip-GANomaly paper
Pebal
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129
[ECCV'22 Oral] Pixel-wise Energy-biased Abstention Learning for Anomaly Segmentation on Complex Urban Driving Scenes
Gpnd
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106
Generative Probabilistic Novelty Detection with Adversarial Autoencoders
Mantranet Pytorch
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101
Implementation of the famous Image Manipulation\Forgery Detector "ManTraNet" in Pytorch
Visual Feature Attribution Using Wasserstein Gans Pytorch
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92
Implementation of Visual Feature Attribution using Wasserstein GANs (VAGANs, https://arxiv.org/abs/1711.08998) in PyTorch
Cyber Security
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89
Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities
F Anogan
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86
Implementation of f-AnoGAN with PyTorch
Keras Oneclassanomalydetection
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79
[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.
Deepai
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74
Detection of Accounting Anomalies using Deep Autoencoder Neural Networks - A lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.
Wgan Gp Anomaly
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73
gan, wgan-gp, anomaly detection, unsupervised, pytorch
Pytorch Cutpaste
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65
unoffical and work in progress PyTorch implementation of CutPaste
Goad
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61
Official implementation of "Classification-Based Anomaly Detection for General Data" by Liron Bergman and Yedid Hoshen, ICLR 2020.
Anodet
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59
Anomaly detection on images using features from pretrained neural networks.
Mahalanobisad Pytorch
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56
PyTorch implementation of "Modeling the Distribution of Normal Data in Pre-Trained Deep Features for Anomaly Detection"
3d Ads
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53
Official Implementation for the "Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detection" paper.
Entropic Out Of Distribution Detection
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47
Add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Perform efficient inferences (i.e., do not increase inference time) and detection without classification accuracy drop, hyperparameter tuning, or collecting additional data.
Ood Detection Using Oecc
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45
Outlier Exposure with Confidence Control for Out-of-Distribution Detection
Od Test
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44
OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)
Ddad
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43
MICCAI 2022 (Early Accepted): Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays
Cutpaste
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36
Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch
Cvae Anomalydetection Pytorch
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36
Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)
Distinction Maximization Loss
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34
Improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in your project! Perform efficient inferences (i.e., do not increase inference time) without repetitive model training, hyperparameter tuning, or collecting additional data.
Msda
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34
multi-dimensional, multi-sensor, multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
Anoshift
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33
Stad
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32
Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings
Stgram Mfn
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32
A spectro-temporal fusion feature, STgram, with MobileFaceNet For more stable Anomalous Sound Detection
Ddad Asr
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30
[MedIA'2023] Dual-distribution discrepancy with self-supervised refinement for anomaly detection in medical images
Ccd
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30
Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]
Vae Anomaly Detector
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29
Experiments on unsupervised anomaly detection using variational autoencoder. The variational autoencoder is implemented in Pytorch.
Quadra
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27
Quadra: Effortless and reproducible deep learning workflows with configuration files.
Ghrn
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26
[WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang
A Hierarchical Transformation Discriminating Generative Model For Few Shot Anomaly Detection
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25
Official pytorch implementation of the paper: "A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection"
Deepad
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25
Detection of Accounting Anomalies in the Latent Space using Adversarial Autoencoder Neural Networks - A lab we prepared for the KDD'19 Workshop on Anomaly Detection in Finance that will walk you through the detection of interpretable accounting anomalies using adversarial autoencoder neural networks. The majority of the lab content is based on Jupyter Notebook, Python and PyTorch.
Vae Torch
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24
Variational autoencoder for anomaly detection (in PyTorch).
Wgan Gp Anomaly
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23
gan, wgan-gp, anomaly detection, unsupervised, pytorch
Coca
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23
Deep Contrastive One-Class Time Series Anomaly Detection
Classification Ad
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22
Repository for the paper "Rethinking Assumptions in Anomaly Detection"
Logdeep
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21
log anomaly detection toolkit including DeepLog
F Anogan_with_pytorch
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20
Semiorthogonal
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19
Unofficial re-implementation of Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation
Anomaly Detection In Industry Manufacturing
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18
Pipeline training and inference Anomalib models UI in Anomaly Detection
Machine Learning
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17
A set of jupyter notebooks
Spade Fast
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16
This is an unofficial implementation of the paper "Sub-Image Anomaly Detection with Deep Pyramid Correspondences".
Gad Nr
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16
[WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction
Compactcnn
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16
PyTorch and Keras implementation of CompactCNN for Anomaly Detection in textured surfaces.
Gcnn
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16
The Pytorch Implementation of GCNN model from paper Fake News Detection on Social Media using Geometric Deep Learning
F Anogan Pytorch
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15
Unofficial PyTorch implementation for f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks.
Fsad Net
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15
Offical code for 'Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy' [MICCAI 2020]
Cvdd Pytorch
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14
A PyTorch implementation of Context Vector Data Description (CVDD), a method for Anomaly Detection on text.
Deeplog
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14
PyTorch implements "DeepLog: Anomaly Detection and Diagnosis from System Logs through Deep Learning"
Gee
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14
Pytorch implementation of GEE: A Gradient-based Explainable Variational Autoencoder for Network Anomaly Detection
Anomaly Detection In Histology
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14
Learning image representations for anomaly detection: application to discovery of histological alterations in drug development
Mc Lstm Time Series
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12
本项目是论文《Anomaly Detection Using Multiscale C-LSTM for Univariate Time-Series》的实验代码,实现了多种时间序列异常检测模型。
Padim
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10
PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization
Pycp_apr
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10
CP-APR Tensor Decomposition with PyTorch backend. pyCP_APR can perform non-negative Poisson Tensor Factorization on GPU, and includes an interface for anomaly detection using the extracted latent patterns.
Robust Deep Learning
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9
Train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.
Anomaly Detection
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9
Anomaly detection from surveillence videos using Deep Multiple Instance Learning
Wsdm_gdn
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9
[WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang
Anomaly Clustering
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8
An unofficial implementation using Pytorch for "Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types". Improve the algorithm with DINO pretrained ViT. Implement algorithms based on PatchCore.
Osraae
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8
Open-set Recognition with Adversarial Autoencoders
Pgn_anomaly_detection
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8
Prior Generating Networks for Anomaly Detection
Dplan_pytorch
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7
This repository contains an implementation of an anomaly detection method called DPLAN, which is based on the reinforcement learning framework. The method is described in the paper "Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data" by Pang et al.
Alocc_mnist
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7
異常検知手法ALOCCの実装 (Chainer, PyTorch)
Autoembedder
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7
PyTorch autoencoder with additional embeddings layer for categorical data 🚘
Eoe
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7
Repository for the Exposing Outlier Exposure paper
Pmad
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7
Pytorch Implementation for AAAI2023 paper: One-for-All: Proposal Masked Cross-Class Anomaly Detection
Ad_fl_dl
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7
Apply Federated Learning and Deep Learning (Deep Auto-encoder) to detect abnormal data for IoT devices.
Tpp Anomaly Detection
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6
Implementation of "Detecting Anomalous Event Sequences with Temporal Point Processes" (NeurIPS 2021)
Wdmt Net
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6
This is an official implementation of 'A Multi-task Network with Weight Decay Skip Connection Training for Anomaly Detection in Retinal Fundus Images'
Anomalydetection.pytorch
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6
Startup some anomaly detection with pytorch!
Heterogeneous_autoencoder_by_quadratic_neurons
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6
Anomaly Crime Activity Detection
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6
Real Time Detection of Anomalous Activity From Videos (mainly crime actvity). Images of the video is trained using AutoEncoder to get the imtermediate feature representation of image & appliend svm model for the bag of such features to detect the anomaly & LSTM to detect the type of Anomaly.
Descargan
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5
Official Pytorch implementation of the paper DeScarGAN
Recurrent_implicit_quantile_networks
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5
Implementation of the Recurrent Implicit Quantile Networks (RIQNs), used as a baseline in the OOD detection in the anomalous RL benchmark
Riad
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5
Reconstruction by Inpainting Based Anomaly Detection
Padim Efficientnetv2
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5
EfficientNetV2 based PaDiM
Dagmm Unsupervised Anomaly Detection
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5
Unsupervised Time Series Anomaly Detection
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